PaddlePaddle / VisualDL

Introduction

VisualDL is a deep learning visualization tool that can help design deep learning jobs.
It includes features such as scalar, parameter distribution, model structure and image visualization.
Currently it is being developed at a high pace.
New features will be continuously added.

At present, most DNN frameworks use Python as their primary language. VisualDL supports Python by nature.
Users can get plentiful visualization results by simply add a few lines of Python code into their model before training.

Besides Python SDK, VisualDL was writen in C++ on the low level. It also provides C++ SDK that
can be integrated into other platforms.

Component

VisualDL now provides 4 components:

graph

scalar

image

histogram

Graph

Graph is compatible with ONNX(Open Neural Network Exchange)[https://github.com/onnx/onnx],
Cooperated with Python SDK, VisualDL can be compatible with most major DNN frameworks, including
PaddlePaddle, PyTorch and MXNet.

Scalar

Scalar can be used to show the trends of error during training.

Image

Image can be used to visualize any tensor or intermediate generated image.

Histogram

Histogram can be used to visualize parameter distribution and trends for any tensor.

SDK

VisualDL provides both Python SDK and C++ SDK in order to fit more use cases.

Python SDK

Below is an example of creating a simple Scalar component and inserting data from different timestamps: